The neurons of the primary visual cortex are highly selective for specific features of the visual image. How this integration is accomplished by the intricate connections of the cortical neurocircuitry is the subject of this proposal. The mechanisms of integration will be studied by recording intracellularly from cortical neurons in the intact cat and analyzing the synaptic potentials evoked by visual stimulation. These experiments directly explore the visual information a neuron receives, from which presynaptic neurons it receives that information, and by what mechanisms the neuron processes the information. Three series of experiments are proposed for the next 5 years of the project. 1) We will explore the origins of cross-orientation suppression. This nonlinear property of simple cells, now 30 years old, represents some of the strongest evidence for feedback models of orientation selectivity in visual cortex. Our preliminary data indicate that cross-orientation suppression might arise not from intracortical inhibition, as is often proposed, but from amplification by threshold of small cross-orientation effects in the relay cells of the lateral geniculate. We will test this proposal by comparing the behavior of relay cells, membrane potential responses and spike rate responses in simple cells. 2) Cortical simple cells exhibit strong contrast-dependent nonlinearities: changes in the amplitude, time course and selectivity of visual responses that occur with increasing stimulus contrast. These nonlinearities, like cross orientation suppressions, appear to be inconsistent with feed forward models of cortical processing. As with cross-orientation suppression, however, we propose to test whether small nonlinear effects in geniculate relay cells, when amplified by spike threshold, might account for the bulk of contrast-dependent nonlinearity in simple cells. 3) Complex cells in cortex exhibit distinct state transitions: abrupt, spontaneous shifts of membrane potential between distinct ranges of potential termed UP and DOWN states. We will examine the interaction between these transitions and visual stimulation, asking whether visual stimuli affect the probability of state transitions, and conversely, whether the current state of a neuron affects the size and latency of visual responses.